Akademik Veri Yönetim Sistemi
APPLIED AND COMPUTATIONAL MATHEMATICS, cilt.25, sa.1, ss.1-38, 2026 (SCI-Expanded, Scopus)
Software-defined networks are next-generation network architectures that offer flexibility, programmability, and centralized management by separating the network control plane from the data plane. However, the openness, dynamic configuration capabilities, and single-point management features of this architectural structure lead to greater information security risks than those in traditional networks. A holistic analysis of risks in software-defined network-based environments requires accurate modeling of these uncertainties. Based on this need, this study proposes a new, hybrid multi-criteria decision-making approach using interval-valued Fermatean fuzzy sets to evaluate information security risks in software-defined networks. The proposed model consists of four stages. In the first stage, the software-defined network architecture and related vulnerabilities are defined. In the second stage, cause-and-effect relationships between criteria are determined using the interval-valued Fermatean fuzzy-DEMATEL method, and criterion weights are calculated using the interval-valued Fermatean fuzzy-AHP method. In the third stage, information security risks on software-defined networks are ranked using the interval-valued Fermatean fuzzy-TOPSIS method. In the final stage, we validated the stability and reliability of the technique through comparative analysis and sensitivity analysis based on interval-valued Fermatean fuzzy-ARAS. The study evaluated five fundamental information security criteria (confidentiality, consistency, integrity, authentication, and availability) and 12 vulnerabilities specific to the software-defined network architecture. According to the results, confidentiality was identified as the most critical risk area, while availability was the least prioritized. Sensitivity analysis showed that the results remained consistent across varying criterion weights. Furthermore, a comparative analysis with interval-valued Fermatean fuzzy-ARAS showed a high degree of overlap with the results obtained with the hybrid method. In conclusion, the developed interval-valued Fermatean fuzzy set-based hybrid multicriteria decision-making approach provides a reliable and applicable decision-support mechanism for risk assessment in uncertain software-defined network environments.